Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = '/data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [2]:
!pip install matplotlib==2.0.2
Collecting matplotlib==2.0.2
  Downloading https://files.pythonhosted.org/packages/60/d4/6b6d8a7a6bc69a1602ab372f6fc6e88ef88a8a96398a1a25edbac636295b/matplotlib-2.0.2-cp36-cp36m-manylinux1_x86_64.whl (14.6MB)
    100% |████████████████████████████████| 14.6MB 47kB/s  eta 0:00:01
Requirement already satisfied: pytz in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: six>=1.10 in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: numpy>=1.7.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.6/site-packages/cycler-0.10.0-py3.6.egg (from matplotlib==2.0.2)
Requirement already satisfied: pyparsing!=2.0.0,!=2.0.4,!=2.1.2,!=2.1.6,>=1.5.6 in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: python-dateutil in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Installing collected packages: matplotlib
  Found existing installation: matplotlib 2.1.0
    Uninstalling matplotlib-2.1.0:
      Successfully uninstalled matplotlib-2.1.0
Successfully installed matplotlib-2.0.2
You are using pip version 9.0.1, however version 10.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
# Note: because of a version problem with matplot lib, the following line of code doesn't work in this workspace.
# pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [4]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[4]:
<matplotlib.image.AxesImage at 0x7f0cb2d3def0>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [5]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.3.0
Default GPU Device: /gpu:0

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [6]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    
    
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    inputs_real = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), name='input_real')
    inputs_z = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
    learning_rate = tf.placeholder(tf.float32, name='learning_rate')

    return inputs_real, inputs_z, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
ERROR:tensorflow:==================================
Object was never used (type <class 'tensorflow.python.framework.ops.Operation'>):
<tf.Operation 'assert_rank_2/Assert/Assert' type=Assert>
If you want to mark it as used call its "mark_used()" method.
It was originally created here:
['File "/opt/conda/lib/python3.6/runpy.py", line 193, in _run_module_as_main\n    "__main__", mod_spec)', 'File "/opt/conda/lib/python3.6/runpy.py", line 85, in _run_code\n    exec(code, run_globals)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py", line 16, in <module>\n    app.launch_new_instance()', 'File "/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance\n    app.start()', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 478, in start\n    self.io_loop.start()', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/ioloop.py", line 177, in start\n    super(ZMQIOLoop, self).start()', 'File "/opt/conda/lib/python3.6/site-packages/tornado/ioloop.py", line 888, in start\n    handler_func(fd_obj, events)', 'File "/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py", line 277, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events\n    self._handle_recv()', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv\n    self._run_callback(callback, msg)', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback\n    callback(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py", line 277, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 281, in dispatcher\n    return self.dispatch_shell(stream, msg)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 232, in dispatch_shell\n    handler(stream, idents, msg)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 397, in execute_request\n    user_expressions, allow_stdin)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 208, in do_execute\n    res = shell.run_cell(code, store_history=store_history, silent=silent)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 533, in run_cell\n    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2728, in run_cell\n    interactivity=interactivity, compiler=compiler, result=result)', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2856, in run_ast_nodes\n    if self.run_code(code, result):', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2910, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)', 'File "<ipython-input-6-d12c5a64cc70>", line 24, in <module>\n    tests.test_model_inputs(model_inputs)', 'File "/home/workspace/face_generation/problem_unittests.py", line 12, in func_wrapper\n    result = func(*args)', 'File "/home/workspace/face_generation/problem_unittests.py", line 68, in test_model_inputs\n    _check_input(learn_rate, [], \'Learning Rate\')', 'File "/home/workspace/face_generation/problem_unittests.py", line 34, in _check_input\n    _assert_tensor_shape(tensor, shape, \'Real Input\')', 'File "/home/workspace/face_generation/problem_unittests.py", line 20, in _assert_tensor_shape\n    assert tf.assert_rank(tensor, len(shape), message=\'{} has wrong rank\'.format(display_name))', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/check_ops.py", line 617, in assert_rank\n    dynamic_condition, data, summarize)', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/check_ops.py", line 571, in _assert_rank_condition\n    return control_flow_ops.Assert(condition, data, summarize=summarize)', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_should_use.py", line 175, in wrapped\n    return _add_should_use_warning(fn(*args, **kwargs))', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_should_use.py", line 144, in _add_should_use_warning\n    wrapped = TFShouldUseWarningWrapper(x)', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_should_use.py", line 101, in __init__\n    stack = [s.strip() for s in traceback.format_stack()]']
==================================
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [16]:
def discriminator(images, reuse=False):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    with tf.variable_scope('discriminator', reuse=reuse):
        alpha = 0.2
        x1 = tf.layers.conv2d(images, 64, 5, strides=2, padding='same')
        relu1 = tf.maximum(alpha * x1, x1)
        
        x2 = tf.layers.conv2d(relu1, 128, 5, strides=2, padding='same')
        bn2 = tf.layers.batch_normalization(x2, training=True)
        relu2 = tf.maximum(alpha * bn2, bn2)
        
        x3 = tf.layers.conv2d(relu2, 256, 5, strides=2, padding='same')
        bn3 = tf.layers.batch_normalization(x3, training=True)
        relu3 = tf.maximum(alpha * bn3, bn3)

        # Flatten it
        flat = tf.reshape(relu3, (-1, 4*4*256))
        logits = tf.layers.dense(flat, 1)
        logits = tf.layers.dropout(logits, rate=0.3)
        out = tf.sigmoid(logits)
        
        return out, logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [27]:
def generator(z, out_channel_dim, is_train=True):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    with tf.variable_scope('generator', reuse = not is_train):
        alpha = 0.2
        # First fully connected layer
        x1 = tf.layers.dense(z, 7*7*512)
        # Reshape it to start the convolutional stack
        x1 = tf.reshape(x1, (-1, 7, 7, 512))
        x1 = tf.layers.batch_normalization(x1, training=is_train)
        x1 = tf.maximum(alpha * x1, x1)

        x2 = tf.layers.conv2d_transpose(x1, 256, 5, strides=2, padding='same')
        x2 = tf.layers.batch_normalization(x2, training=is_train)
        x2 = tf.maximum(alpha * x2, x2)
        
        x3 = tf.layers.conv2d_transpose(x2, 128, 5, strides=1, padding='same')
        x3 = tf.layers.batch_normalization(x3, training=is_train)
        x3 = tf.maximum(alpha * x3, x3)
        
#         x4 = tf.layers.conv2d_transpose(x3, 56, 5, strides=2, padding='same')
#         x4 = tf.layers.batch_normalization(x4, training=is_train)
#         x4 = tf.maximum(alpha * x4, x4)

        # Output layer
        logits = tf.layers.conv2d_transpose(x3, out_channel_dim, 5, strides=2, padding='same')

        out = tf.tanh(logits)
        return out
    


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [29]:
def model_loss(input_real, input_z, out_channel_dim):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    
    g_model = generator(input_z, out_channel_dim)
    d_model_real, d_logits_real = discriminator(input_real)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
    smooth = 0.1
    d_loss_real = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)*(1 - smooth)))
    d_loss_fake = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
    g_loss = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))

    d_loss = d_loss_real + d_loss_fake
    
    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [30]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    
    # Get weights and bias to update
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]

    # Optimize
    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
    
    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [31]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [33]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    image_width = data_shape[1]
    image_height = data_shape[2]
    image_channels = data_shape[3]
    input_real, input_z, _ = model_inputs(image_width, image_height, image_channels, z_dim)
    d_loss, g_loss = model_loss(input_real, input_z, image_channels)
    d_train_opt, g_train_opt = model_opt(d_loss, g_loss, learning_rate, beta1)
    print_every = 10
    show_every = 100
    losses = []
    steps = 0
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                batch_images = 2*batch_images
                steps += 1
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))

                _ = sess.run(d_train_opt, feed_dict={input_real: batch_images, input_z: batch_z})
                _ = sess.run(g_train_opt, feed_dict={input_z: batch_z, input_real: batch_images})

                if steps % print_every == 0:
                    train_loss_d = d_loss.eval({input_z: batch_z, input_real: batch_images})
                    train_loss_g = g_loss.eval({input_real: batch_images, input_z: batch_z})

                    print("Epoch {}/{}...".format(epoch_i+1, epoch_count),
                          "Discriminator Loss: {:.4f}...".format(train_loss_d),
                          "Generator Loss: {:.4f}".format(train_loss_g))
                    losses.append((train_loss_d, train_loss_g))

                if steps % show_every == 0:
                    show_generator_output(sess, n_images = 25, input_z = input_z, out_channel_dim = image_channels , image_mode = data_image_mode)
                    
                
                

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [34]:
batch_size = 32
z_dim = 100
learning_rate = 0.0001
beta1 = 0.3


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1/2... Discriminator Loss: 1.9878... Generator Loss: 0.2721
Epoch 1/2... Discriminator Loss: 2.1009... Generator Loss: 0.2035
Epoch 1/2... Discriminator Loss: 1.3029... Generator Loss: 0.6082
Epoch 1/2... Discriminator Loss: 1.3723... Generator Loss: 0.8672
Epoch 1/2... Discriminator Loss: 1.1797... Generator Loss: 0.6631
Epoch 1/2... Discriminator Loss: 1.6960... Generator Loss: 0.3365
Epoch 1/2... Discriminator Loss: 1.4788... Generator Loss: 0.4296
Epoch 1/2... Discriminator Loss: 1.5512... Generator Loss: 1.8865
Epoch 1/2... Discriminator Loss: 1.4313... Generator Loss: 0.4868
Epoch 1/2... Discriminator Loss: 1.3013... Generator Loss: 0.6262
Epoch 1/2... Discriminator Loss: 1.3220... Generator Loss: 1.4706
Epoch 1/2... Discriminator Loss: 1.7176... Generator Loss: 0.3172
Epoch 1/2... Discriminator Loss: 1.3600... Generator Loss: 0.5058
Epoch 1/2... Discriminator Loss: 1.3110... Generator Loss: 0.5628
Epoch 1/2... Discriminator Loss: 1.6312... Generator Loss: 0.3564
Epoch 1/2... Discriminator Loss: 1.6136... Generator Loss: 0.3579
Epoch 1/2... Discriminator Loss: 1.3664... Generator Loss: 0.4963
Epoch 1/2... Discriminator Loss: 1.2673... Generator Loss: 1.7158
Epoch 1/2... Discriminator Loss: 1.1136... Generator Loss: 1.1459
Epoch 1/2... Discriminator Loss: 1.1367... Generator Loss: 1.9286
Epoch 1/2... Discriminator Loss: 0.9659... Generator Loss: 1.3066
Epoch 1/2... Discriminator Loss: 1.2689... Generator Loss: 1.9794
Epoch 1/2... Discriminator Loss: 1.0470... Generator Loss: 1.1042
Epoch 1/2... Discriminator Loss: 1.1164... Generator Loss: 1.5125
Epoch 1/2... Discriminator Loss: 1.1944... Generator Loss: 0.6200
Epoch 1/2... Discriminator Loss: 1.1675... Generator Loss: 0.6774
Epoch 1/2... Discriminator Loss: 0.9877... Generator Loss: 1.3233
Epoch 1/2... Discriminator Loss: 1.1573... Generator Loss: 1.2872
Epoch 1/2... Discriminator Loss: 1.1564... Generator Loss: 0.6743
Epoch 1/2... Discriminator Loss: 0.9528... Generator Loss: 1.6524
Epoch 1/2... Discriminator Loss: 1.0375... Generator Loss: 0.8332
Epoch 1/2... Discriminator Loss: 1.0895... Generator Loss: 0.8377
Epoch 1/2... Discriminator Loss: 1.0291... Generator Loss: 0.8341
Epoch 1/2... Discriminator Loss: 0.9788... Generator Loss: 1.6544
Epoch 1/2... Discriminator Loss: 0.9766... Generator Loss: 1.1390
Epoch 1/2... Discriminator Loss: 1.0420... Generator Loss: 1.8019
Epoch 1/2... Discriminator Loss: 1.3681... Generator Loss: 0.4921
Epoch 1/2... Discriminator Loss: 1.1252... Generator Loss: 0.7123
Epoch 1/2... Discriminator Loss: 0.9760... Generator Loss: 1.4804
Epoch 1/2... Discriminator Loss: 0.9976... Generator Loss: 1.3065
Epoch 1/2... Discriminator Loss: 1.0837... Generator Loss: 1.6852
Epoch 1/2... Discriminator Loss: 0.8535... Generator Loss: 1.3798
Epoch 1/2... Discriminator Loss: 1.1758... Generator Loss: 0.6640
Epoch 1/2... Discriminator Loss: 0.9556... Generator Loss: 0.9984
Epoch 1/2... Discriminator Loss: 1.4210... Generator Loss: 0.4707
Epoch 1/2... Discriminator Loss: 0.9517... Generator Loss: 0.9053
Epoch 1/2... Discriminator Loss: 0.9154... Generator Loss: 1.1998
Epoch 1/2... Discriminator Loss: 1.1010... Generator Loss: 2.0887
Epoch 1/2... Discriminator Loss: 0.9292... Generator Loss: 1.0124
Epoch 1/2... Discriminator Loss: 1.1547... Generator Loss: 2.0502
Epoch 1/2... Discriminator Loss: 1.4722... Generator Loss: 0.4410
Epoch 1/2... Discriminator Loss: 1.1772... Generator Loss: 0.6419
Epoch 1/2... Discriminator Loss: 1.2817... Generator Loss: 0.5481
Epoch 1/2... Discriminator Loss: 1.1827... Generator Loss: 0.6667
Epoch 1/2... Discriminator Loss: 0.9331... Generator Loss: 1.5164
Epoch 1/2... Discriminator Loss: 1.0673... Generator Loss: 0.7806
Epoch 1/2... Discriminator Loss: 1.0287... Generator Loss: 1.1853
Epoch 1/2... Discriminator Loss: 0.9462... Generator Loss: 1.5107
Epoch 1/2... Discriminator Loss: 1.5067... Generator Loss: 0.4338
Epoch 1/2... Discriminator Loss: 0.8926... Generator Loss: 1.4205
Epoch 1/2... Discriminator Loss: 1.4791... Generator Loss: 0.4405
Epoch 1/2... Discriminator Loss: 1.4812... Generator Loss: 0.4322
Epoch 1/2... Discriminator Loss: 0.9365... Generator Loss: 1.2969
Epoch 1/2... Discriminator Loss: 0.9831... Generator Loss: 1.2492
Epoch 1/2... Discriminator Loss: 1.0215... Generator Loss: 1.2595
Epoch 1/2... Discriminator Loss: 1.0766... Generator Loss: 0.8453
Epoch 1/2... Discriminator Loss: 0.9624... Generator Loss: 1.1263
Epoch 1/2... Discriminator Loss: 1.4490... Generator Loss: 2.5957
Epoch 1/2... Discriminator Loss: 1.0119... Generator Loss: 1.2869
Epoch 1/2... Discriminator Loss: 0.9856... Generator Loss: 1.0062
Epoch 1/2... Discriminator Loss: 1.0301... Generator Loss: 0.8140
Epoch 1/2... Discriminator Loss: 1.0362... Generator Loss: 1.0427
Epoch 1/2... Discriminator Loss: 1.1508... Generator Loss: 0.6938
Epoch 1/2... Discriminator Loss: 0.9658... Generator Loss: 1.0031
Epoch 1/2... Discriminator Loss: 1.6639... Generator Loss: 0.3562
Epoch 1/2... Discriminator Loss: 1.1672... Generator Loss: 1.0413
Epoch 1/2... Discriminator Loss: 1.4531... Generator Loss: 0.4380
Epoch 1/2... Discriminator Loss: 0.9189... Generator Loss: 1.2301
Epoch 1/2... Discriminator Loss: 1.2238... Generator Loss: 0.6181
Epoch 1/2... Discriminator Loss: 1.0289... Generator Loss: 0.8680
Epoch 1/2... Discriminator Loss: 0.9495... Generator Loss: 0.9355
Epoch 1/2... Discriminator Loss: 1.0553... Generator Loss: 1.0768
Epoch 1/2... Discriminator Loss: 1.0434... Generator Loss: 1.1039
Epoch 1/2... Discriminator Loss: 1.0530... Generator Loss: 1.0593
Epoch 1/2... Discriminator Loss: 1.2176... Generator Loss: 1.6350
Epoch 1/2... Discriminator Loss: 1.0824... Generator Loss: 0.7164
Epoch 1/2... Discriminator Loss: 1.0453... Generator Loss: 0.8276
Epoch 1/2... Discriminator Loss: 1.1200... Generator Loss: 1.3282
Epoch 1/2... Discriminator Loss: 1.4090... Generator Loss: 0.4629
Epoch 1/2... Discriminator Loss: 1.2457... Generator Loss: 1.9932
Epoch 1/2... Discriminator Loss: 1.2798... Generator Loss: 0.5597
Epoch 1/2... Discriminator Loss: 1.0888... Generator Loss: 0.8827
Epoch 1/2... Discriminator Loss: 1.2196... Generator Loss: 0.6657
Epoch 1/2... Discriminator Loss: 1.1793... Generator Loss: 0.7446
Epoch 1/2... Discriminator Loss: 1.1348... Generator Loss: 0.8735
Epoch 1/2... Discriminator Loss: 1.0907... Generator Loss: 1.4071
Epoch 1/2... Discriminator Loss: 1.0492... Generator Loss: 0.9842
Epoch 1/2... Discriminator Loss: 0.9699... Generator Loss: 1.0439
Epoch 1/2... Discriminator Loss: 1.2212... Generator Loss: 0.7353
Epoch 1/2... Discriminator Loss: 1.3732... Generator Loss: 0.5101
Epoch 1/2... Discriminator Loss: 1.0179... Generator Loss: 0.9154
Epoch 1/2... Discriminator Loss: 0.9846... Generator Loss: 1.2179
Epoch 1/2... Discriminator Loss: 1.1178... Generator Loss: 1.3839
Epoch 1/2... Discriminator Loss: 1.1550... Generator Loss: 0.8021
Epoch 1/2... Discriminator Loss: 1.0535... Generator Loss: 0.8599
Epoch 1/2... Discriminator Loss: 0.9381... Generator Loss: 0.9217
Epoch 1/2... Discriminator Loss: 1.0634... Generator Loss: 1.5533
Epoch 1/2... Discriminator Loss: 1.4728... Generator Loss: 0.5078
Epoch 1/2... Discriminator Loss: 1.2541... Generator Loss: 0.6157
Epoch 1/2... Discriminator Loss: 1.0754... Generator Loss: 0.7851
Epoch 1/2... Discriminator Loss: 1.2417... Generator Loss: 0.6076
Epoch 1/2... Discriminator Loss: 1.2498... Generator Loss: 0.5621
Epoch 1/2... Discriminator Loss: 1.0365... Generator Loss: 0.8792
Epoch 1/2... Discriminator Loss: 1.1668... Generator Loss: 0.6953
Epoch 1/2... Discriminator Loss: 0.9818... Generator Loss: 0.8988
Epoch 1/2... Discriminator Loss: 1.3107... Generator Loss: 0.6034
Epoch 1/2... Discriminator Loss: 0.9590... Generator Loss: 1.1279
Epoch 1/2... Discriminator Loss: 1.0339... Generator Loss: 1.5942
Epoch 1/2... Discriminator Loss: 0.9936... Generator Loss: 1.6990
Epoch 1/2... Discriminator Loss: 1.3578... Generator Loss: 0.4999
Epoch 1/2... Discriminator Loss: 1.1557... Generator Loss: 1.5955
Epoch 1/2... Discriminator Loss: 0.9836... Generator Loss: 1.2144
Epoch 1/2... Discriminator Loss: 1.0869... Generator Loss: 0.7502
Epoch 1/2... Discriminator Loss: 1.0235... Generator Loss: 1.4293
Epoch 1/2... Discriminator Loss: 1.1055... Generator Loss: 0.7354
Epoch 1/2... Discriminator Loss: 1.1579... Generator Loss: 0.8835
Epoch 1/2... Discriminator Loss: 1.1293... Generator Loss: 1.6967
Epoch 1/2... Discriminator Loss: 1.1662... Generator Loss: 0.7428
Epoch 1/2... Discriminator Loss: 0.9665... Generator Loss: 0.9452
Epoch 1/2... Discriminator Loss: 0.9849... Generator Loss: 1.6653
Epoch 1/2... Discriminator Loss: 1.0043... Generator Loss: 0.8987
Epoch 1/2... Discriminator Loss: 1.0144... Generator Loss: 0.9342
Epoch 1/2... Discriminator Loss: 0.9478... Generator Loss: 1.1001
Epoch 1/2... Discriminator Loss: 1.0084... Generator Loss: 0.9700
Epoch 1/2... Discriminator Loss: 1.8851... Generator Loss: 0.3097
Epoch 1/2... Discriminator Loss: 1.0559... Generator Loss: 0.7995
Epoch 1/2... Discriminator Loss: 0.9559... Generator Loss: 1.0682
Epoch 1/2... Discriminator Loss: 1.1848... Generator Loss: 0.6776
Epoch 1/2... Discriminator Loss: 0.9695... Generator Loss: 1.1391
Epoch 1/2... Discriminator Loss: 2.1443... Generator Loss: 2.3262
Epoch 1/2... Discriminator Loss: 1.0639... Generator Loss: 0.7834
Epoch 1/2... Discriminator Loss: 1.0063... Generator Loss: 1.3236
Epoch 1/2... Discriminator Loss: 0.9591... Generator Loss: 1.0859
Epoch 1/2... Discriminator Loss: 1.2954... Generator Loss: 0.5317
Epoch 1/2... Discriminator Loss: 1.1323... Generator Loss: 0.6895
Epoch 1/2... Discriminator Loss: 1.4232... Generator Loss: 0.4738
Epoch 1/2... Discriminator Loss: 0.9834... Generator Loss: 1.8074
Epoch 1/2... Discriminator Loss: 0.9510... Generator Loss: 0.9804
Epoch 1/2... Discriminator Loss: 0.9774... Generator Loss: 1.0556
Epoch 1/2... Discriminator Loss: 1.0427... Generator Loss: 0.7831
Epoch 1/2... Discriminator Loss: 1.0283... Generator Loss: 0.8081
Epoch 1/2... Discriminator Loss: 0.7959... Generator Loss: 1.3934
Epoch 1/2... Discriminator Loss: 1.3208... Generator Loss: 1.8881
Epoch 1/2... Discriminator Loss: 1.0917... Generator Loss: 0.9021
Epoch 1/2... Discriminator Loss: 1.0113... Generator Loss: 1.7441
Epoch 1/2... Discriminator Loss: 1.0388... Generator Loss: 0.7869
Epoch 1/2... Discriminator Loss: 1.0138... Generator Loss: 0.7943
Epoch 1/2... Discriminator Loss: 0.8685... Generator Loss: 1.0949
Epoch 1/2... Discriminator Loss: 0.9965... Generator Loss: 1.1046
Epoch 1/2... Discriminator Loss: 1.6852... Generator Loss: 0.3421
Epoch 1/2... Discriminator Loss: 0.9967... Generator Loss: 0.9682
Epoch 1/2... Discriminator Loss: 1.3159... Generator Loss: 0.5456
Epoch 1/2... Discriminator Loss: 1.1913... Generator Loss: 0.6542
Epoch 1/2... Discriminator Loss: 0.9477... Generator Loss: 1.2652
Epoch 1/2... Discriminator Loss: 1.3378... Generator Loss: 0.5223
Epoch 1/2... Discriminator Loss: 0.9174... Generator Loss: 1.2273
Epoch 1/2... Discriminator Loss: 0.9387... Generator Loss: 0.9106
Epoch 1/2... Discriminator Loss: 0.9478... Generator Loss: 1.2387
Epoch 1/2... Discriminator Loss: 0.9249... Generator Loss: 0.9906
Epoch 1/2... Discriminator Loss: 0.8632... Generator Loss: 1.0279
Epoch 1/2... Discriminator Loss: 3.4056... Generator Loss: 0.0785
Epoch 1/2... Discriminator Loss: 1.0708... Generator Loss: 1.3412
Epoch 1/2... Discriminator Loss: 0.8672... Generator Loss: 1.2192
Epoch 1/2... Discriminator Loss: 0.9770... Generator Loss: 0.8403
Epoch 1/2... Discriminator Loss: 0.9288... Generator Loss: 1.2841
Epoch 1/2... Discriminator Loss: 1.8117... Generator Loss: 3.0238
Epoch 1/2... Discriminator Loss: 1.0136... Generator Loss: 0.8507
Epoch 1/2... Discriminator Loss: 0.8265... Generator Loss: 1.2396
Epoch 1/2... Discriminator Loss: 0.8843... Generator Loss: 1.0876
Epoch 1/2... Discriminator Loss: 0.9339... Generator Loss: 1.1193
Epoch 1/2... Discriminator Loss: 1.3751... Generator Loss: 0.5058
Epoch 1/2... Discriminator Loss: 0.8189... Generator Loss: 1.3393
Epoch 1/2... Discriminator Loss: 1.5822... Generator Loss: 0.4015
Epoch 1/2... Discriminator Loss: 0.8963... Generator Loss: 1.0956
Epoch 1/2... Discriminator Loss: 1.2681... Generator Loss: 0.5632
Epoch 1/2... Discriminator Loss: 0.9758... Generator Loss: 0.9564
Epoch 1/2... Discriminator Loss: 1.0307... Generator Loss: 0.8127
Epoch 2/2... Discriminator Loss: 0.9980... Generator Loss: 0.8961
Epoch 2/2... Discriminator Loss: 2.1473... Generator Loss: 0.2494
Epoch 2/2... Discriminator Loss: 1.1895... Generator Loss: 0.6208
Epoch 2/2... Discriminator Loss: 1.1019... Generator Loss: 0.7130
Epoch 2/2... Discriminator Loss: 1.0324... Generator Loss: 0.8051
Epoch 2/2... Discriminator Loss: 1.0956... Generator Loss: 0.7063
Epoch 2/2... Discriminator Loss: 0.8913... Generator Loss: 1.2731
Epoch 2/2... Discriminator Loss: 0.8484... Generator Loss: 1.0399
Epoch 2/2... Discriminator Loss: 1.3120... Generator Loss: 0.5546
Epoch 2/2... Discriminator Loss: 1.6678... Generator Loss: 0.3856
Epoch 2/2... Discriminator Loss: 0.9421... Generator Loss: 1.0571
Epoch 2/2... Discriminator Loss: 1.5603... Generator Loss: 0.3982
Epoch 2/2... Discriminator Loss: 0.9334... Generator Loss: 1.1582
Epoch 2/2... Discriminator Loss: 1.1588... Generator Loss: 0.6450
Epoch 2/2... Discriminator Loss: 0.9394... Generator Loss: 0.9204
Epoch 2/2... Discriminator Loss: 1.0728... Generator Loss: 0.7443
Epoch 2/2... Discriminator Loss: 1.0408... Generator Loss: 0.8072
Epoch 2/2... Discriminator Loss: 1.4935... Generator Loss: 0.4208
Epoch 2/2... Discriminator Loss: 0.9277... Generator Loss: 1.0894
Epoch 2/2... Discriminator Loss: 1.2303... Generator Loss: 0.5915
Epoch 2/2... Discriminator Loss: 0.8662... Generator Loss: 1.1037
Epoch 2/2... Discriminator Loss: 1.0447... Generator Loss: 0.8306
Epoch 2/2... Discriminator Loss: 0.9926... Generator Loss: 0.9128
Epoch 2/2... Discriminator Loss: 0.7923... Generator Loss: 1.1720
Epoch 2/2... Discriminator Loss: 0.9277... Generator Loss: 0.9405
Epoch 2/2... Discriminator Loss: 0.9378... Generator Loss: 0.9618
Epoch 2/2... Discriminator Loss: 0.8973... Generator Loss: 1.0859
Epoch 2/2... Discriminator Loss: 1.4185... Generator Loss: 0.4976
Epoch 2/2... Discriminator Loss: 0.9068... Generator Loss: 1.0763
Epoch 2/2... Discriminator Loss: 0.8727... Generator Loss: 1.0945
Epoch 2/2... Discriminator Loss: 1.0237... Generator Loss: 0.8062
Epoch 2/2... Discriminator Loss: 1.5016... Generator Loss: 0.4274
Epoch 2/2... Discriminator Loss: 0.9863... Generator Loss: 0.9199
Epoch 2/2... Discriminator Loss: 1.0034... Generator Loss: 0.9015
Epoch 2/2... Discriminator Loss: 0.9390... Generator Loss: 1.0179
Epoch 2/2... Discriminator Loss: 0.9184... Generator Loss: 0.9154
Epoch 2/2... Discriminator Loss: 3.4258... Generator Loss: 0.0887
Epoch 2/2... Discriminator Loss: 0.8731... Generator Loss: 1.2244
Epoch 2/2... Discriminator Loss: 0.8878... Generator Loss: 1.1560
Epoch 2/2... Discriminator Loss: 0.8392... Generator Loss: 1.1153
Epoch 2/2... Discriminator Loss: 1.5815... Generator Loss: 0.3795
Epoch 2/2... Discriminator Loss: 0.9037... Generator Loss: 1.0150
Epoch 2/2... Discriminator Loss: 1.2302... Generator Loss: 0.5837
Epoch 2/2... Discriminator Loss: 0.8536... Generator Loss: 1.0780
Epoch 2/2... Discriminator Loss: 1.2742... Generator Loss: 0.5769
Epoch 2/2... Discriminator Loss: 1.3263... Generator Loss: 0.5383
Epoch 2/2... Discriminator Loss: 0.9595... Generator Loss: 1.0845
Epoch 2/2... Discriminator Loss: 0.9446... Generator Loss: 0.9188
Epoch 2/2... Discriminator Loss: 0.8851... Generator Loss: 1.0062
Epoch 2/2... Discriminator Loss: 0.9820... Generator Loss: 0.8913
Epoch 2/2... Discriminator Loss: 1.1079... Generator Loss: 1.6284
Epoch 2/2... Discriminator Loss: 1.0420... Generator Loss: 0.8831
Epoch 2/2... Discriminator Loss: 0.8825... Generator Loss: 1.0829
Epoch 2/2... Discriminator Loss: 1.0019... Generator Loss: 0.9546
Epoch 2/2... Discriminator Loss: 1.1780... Generator Loss: 0.6386
Epoch 2/2... Discriminator Loss: 0.8589... Generator Loss: 1.1842
Epoch 2/2... Discriminator Loss: 0.8471... Generator Loss: 1.1397
Epoch 2/2... Discriminator Loss: 0.9451... Generator Loss: 0.9164
Epoch 2/2... Discriminator Loss: 0.7315... Generator Loss: 1.6212
Epoch 2/2... Discriminator Loss: 1.2424... Generator Loss: 0.5986
Epoch 2/2... Discriminator Loss: 2.2926... Generator Loss: 0.1934
Epoch 2/2... Discriminator Loss: 0.8692... Generator Loss: 1.2077
Epoch 2/2... Discriminator Loss: 1.1858... Generator Loss: 0.6595
Epoch 2/2... Discriminator Loss: 0.7400... Generator Loss: 1.4544
Epoch 2/2... Discriminator Loss: 1.0606... Generator Loss: 0.7424
Epoch 2/2... Discriminator Loss: 1.0630... Generator Loss: 0.7494
Epoch 2/2... Discriminator Loss: 0.8937... Generator Loss: 1.0804
Epoch 2/2... Discriminator Loss: 1.2958... Generator Loss: 0.5443
Epoch 2/2... Discriminator Loss: 1.1215... Generator Loss: 0.7106
Epoch 2/2... Discriminator Loss: 0.9506... Generator Loss: 0.9891
Epoch 2/2... Discriminator Loss: 1.3273... Generator Loss: 0.5416
Epoch 2/2... Discriminator Loss: 0.9161... Generator Loss: 1.0271
Epoch 2/2... Discriminator Loss: 1.0781... Generator Loss: 0.7607
Epoch 2/2... Discriminator Loss: 0.8933... Generator Loss: 1.4007
Epoch 2/2... Discriminator Loss: 1.4246... Generator Loss: 0.4704
Epoch 2/2... Discriminator Loss: 0.9309... Generator Loss: 1.0014
Epoch 2/2... Discriminator Loss: 0.9374... Generator Loss: 1.0309
Epoch 2/2... Discriminator Loss: 0.6789... Generator Loss: 1.5825
Epoch 2/2... Discriminator Loss: 1.0737... Generator Loss: 0.7214
Epoch 2/2... Discriminator Loss: 0.8735... Generator Loss: 1.3682
Epoch 2/2... Discriminator Loss: 1.3595... Generator Loss: 2.3393
Epoch 2/2... Discriminator Loss: 0.7983... Generator Loss: 1.5611
Epoch 2/2... Discriminator Loss: 0.8993... Generator Loss: 1.3646
Epoch 2/2... Discriminator Loss: 0.8162... Generator Loss: 1.1752
Epoch 2/2... Discriminator Loss: 1.0593... Generator Loss: 0.7339
Epoch 2/2... Discriminator Loss: 0.9037... Generator Loss: 1.0537
Epoch 2/2... Discriminator Loss: 0.7831... Generator Loss: 1.5511
Epoch 2/2... Discriminator Loss: 0.8152... Generator Loss: 1.1932
Epoch 2/2... Discriminator Loss: 0.7650... Generator Loss: 1.2043
Epoch 2/2... Discriminator Loss: 2.9155... Generator Loss: 0.1658
Epoch 2/2... Discriminator Loss: 0.7214... Generator Loss: 1.5080
Epoch 2/2... Discriminator Loss: 0.8950... Generator Loss: 1.0052
Epoch 2/2... Discriminator Loss: 1.0642... Generator Loss: 0.7372
Epoch 2/2... Discriminator Loss: 1.1292... Generator Loss: 0.7945
Epoch 2/2... Discriminator Loss: 0.7506... Generator Loss: 1.4246
Epoch 2/2... Discriminator Loss: 1.4936... Generator Loss: 0.4426
Epoch 2/2... Discriminator Loss: 0.7315... Generator Loss: 1.3391
Epoch 2/2... Discriminator Loss: 0.7606... Generator Loss: 1.5517
Epoch 2/2... Discriminator Loss: 0.6163... Generator Loss: 1.7011
Epoch 2/2... Discriminator Loss: 0.6738... Generator Loss: 1.5721
Epoch 2/2... Discriminator Loss: 0.8550... Generator Loss: 1.1719
Epoch 2/2... Discriminator Loss: 0.7760... Generator Loss: 1.8434
Epoch 2/2... Discriminator Loss: 1.1011... Generator Loss: 0.7653
Epoch 2/2... Discriminator Loss: 0.7173... Generator Loss: 1.6785
Epoch 2/2... Discriminator Loss: 0.8131... Generator Loss: 1.1427
Epoch 2/2... Discriminator Loss: 0.9039... Generator Loss: 1.0681
Epoch 2/2... Discriminator Loss: 0.7758... Generator Loss: 1.3626
Epoch 2/2... Discriminator Loss: 0.8951... Generator Loss: 1.8039
Epoch 2/2... Discriminator Loss: 0.8455... Generator Loss: 1.0879
Epoch 2/2... Discriminator Loss: 0.7896... Generator Loss: 1.3741
Epoch 2/2... Discriminator Loss: 0.8067... Generator Loss: 1.0917
Epoch 2/2... Discriminator Loss: 0.9315... Generator Loss: 0.9867
Epoch 2/2... Discriminator Loss: 0.9245... Generator Loss: 0.8861
Epoch 2/2... Discriminator Loss: 2.9358... Generator Loss: 0.1240
Epoch 2/2... Discriminator Loss: 1.2772... Generator Loss: 0.6000
Epoch 2/2... Discriminator Loss: 0.8795... Generator Loss: 0.9493
Epoch 2/2... Discriminator Loss: 1.0945... Generator Loss: 0.7703
Epoch 2/2... Discriminator Loss: 1.2014... Generator Loss: 0.6397
Epoch 2/2... Discriminator Loss: 0.8667... Generator Loss: 1.2691
Epoch 2/2... Discriminator Loss: 0.8359... Generator Loss: 1.9453
Epoch 2/2... Discriminator Loss: 0.8891... Generator Loss: 1.2430
Epoch 2/2... Discriminator Loss: 0.8334... Generator Loss: 1.2346
Epoch 2/2... Discriminator Loss: 1.0065... Generator Loss: 0.8212
Epoch 2/2... Discriminator Loss: 0.8000... Generator Loss: 1.0901
Epoch 2/2... Discriminator Loss: 1.0910... Generator Loss: 0.8138
Epoch 2/2... Discriminator Loss: 1.0870... Generator Loss: 0.7020
Epoch 2/2... Discriminator Loss: 2.1258... Generator Loss: 0.2427
Epoch 2/2... Discriminator Loss: 1.0688... Generator Loss: 0.7572
Epoch 2/2... Discriminator Loss: 0.8779... Generator Loss: 1.1259
Epoch 2/2... Discriminator Loss: 1.1117... Generator Loss: 0.6932
Epoch 2/2... Discriminator Loss: 0.9735... Generator Loss: 0.8540
Epoch 2/2... Discriminator Loss: 1.0459... Generator Loss: 0.7562
Epoch 2/2... Discriminator Loss: 0.7473... Generator Loss: 1.4263
Epoch 2/2... Discriminator Loss: 1.2619... Generator Loss: 0.5849
Epoch 2/2... Discriminator Loss: 0.7436... Generator Loss: 1.4053
Epoch 2/2... Discriminator Loss: 1.0183... Generator Loss: 0.8102
Epoch 2/2... Discriminator Loss: 1.1365... Generator Loss: 0.6939
Epoch 2/2... Discriminator Loss: 1.4406... Generator Loss: 0.4637
Epoch 2/2... Discriminator Loss: 0.8292... Generator Loss: 1.6230
Epoch 2/2... Discriminator Loss: 1.0869... Generator Loss: 0.7481
Epoch 2/2... Discriminator Loss: 0.9393... Generator Loss: 1.1090
Epoch 2/2... Discriminator Loss: 0.9105... Generator Loss: 0.9748
Epoch 2/2... Discriminator Loss: 0.8660... Generator Loss: 1.0624
Epoch 2/2... Discriminator Loss: 0.8399... Generator Loss: 1.6388
Epoch 2/2... Discriminator Loss: 0.9517... Generator Loss: 0.9541
Epoch 2/2... Discriminator Loss: 0.8943... Generator Loss: 0.9345
Epoch 2/2... Discriminator Loss: 1.1818... Generator Loss: 0.6397
Epoch 2/2... Discriminator Loss: 0.8697... Generator Loss: 1.0016
Epoch 2/2... Discriminator Loss: 0.8077... Generator Loss: 1.1415
Epoch 2/2... Discriminator Loss: 0.9950... Generator Loss: 0.8069
Epoch 2/2... Discriminator Loss: 0.7372... Generator Loss: 1.7421
Epoch 2/2... Discriminator Loss: 0.9289... Generator Loss: 1.0391
Epoch 2/2... Discriminator Loss: 0.7975... Generator Loss: 1.1458
Epoch 2/2... Discriminator Loss: 2.4595... Generator Loss: 0.1823
Epoch 2/2... Discriminator Loss: 0.9959... Generator Loss: 0.8881
Epoch 2/2... Discriminator Loss: 0.9859... Generator Loss: 0.8202
Epoch 2/2... Discriminator Loss: 0.8571... Generator Loss: 1.1352
Epoch 2/2... Discriminator Loss: 0.8553... Generator Loss: 1.0580
Epoch 2/2... Discriminator Loss: 1.1780... Generator Loss: 0.6841
Epoch 2/2... Discriminator Loss: 0.6173... Generator Loss: 1.6409
Epoch 2/2... Discriminator Loss: 0.7349... Generator Loss: 1.2758
Epoch 2/2... Discriminator Loss: 0.9603... Generator Loss: 0.9201
Epoch 2/2... Discriminator Loss: 0.8097... Generator Loss: 1.0768
Epoch 2/2... Discriminator Loss: 1.1956... Generator Loss: 0.6627
Epoch 2/2... Discriminator Loss: 1.0222... Generator Loss: 0.8124
Epoch 2/2... Discriminator Loss: 0.7766... Generator Loss: 1.3299
Epoch 2/2... Discriminator Loss: 0.9123... Generator Loss: 1.2875
Epoch 2/2... Discriminator Loss: 1.1321... Generator Loss: 1.8644
Epoch 2/2... Discriminator Loss: 0.8252... Generator Loss: 1.1490
Epoch 2/2... Discriminator Loss: 0.6548... Generator Loss: 1.5446
Epoch 2/2... Discriminator Loss: 0.8205... Generator Loss: 2.1710
Epoch 2/2... Discriminator Loss: 1.1663... Generator Loss: 0.6535
Epoch 2/2... Discriminator Loss: 0.8289... Generator Loss: 1.1523
Epoch 2/2... Discriminator Loss: 1.6842... Generator Loss: 0.3515
Epoch 2/2... Discriminator Loss: 0.7654... Generator Loss: 1.4819
Epoch 2/2... Discriminator Loss: 0.8609... Generator Loss: 1.0653
Epoch 2/2... Discriminator Loss: 0.8090... Generator Loss: 1.1745
Epoch 2/2... Discriminator Loss: 0.6547... Generator Loss: 1.4455
Epoch 2/2... Discriminator Loss: 0.6715... Generator Loss: 1.9248
Epoch 2/2... Discriminator Loss: 0.8040... Generator Loss: 1.2062
Epoch 2/2... Discriminator Loss: 0.6989... Generator Loss: 1.5146
Epoch 2/2... Discriminator Loss: 0.8423... Generator Loss: 1.1159
Epoch 2/2... Discriminator Loss: 0.9954... Generator Loss: 0.8652
Epoch 2/2... Discriminator Loss: 0.6940... Generator Loss: 1.3808
Epoch 2/2... Discriminator Loss: 0.7959... Generator Loss: 1.3362
Epoch 2/2... Discriminator Loss: 0.9815... Generator Loss: 1.8384
Epoch 2/2... Discriminator Loss: 0.9072... Generator Loss: 1.1309
Epoch 2/2... Discriminator Loss: 0.9524... Generator Loss: 1.4006

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [36]:
batch_size = 32
z_dim = 100
learning_rate = 0.0001
beta1 = 0.3


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1/1... Discriminator Loss: 3.3779... Generator Loss: 0.0811
Epoch 1/1... Discriminator Loss: 2.1460... Generator Loss: 0.2646
Epoch 1/1... Discriminator Loss: 2.1767... Generator Loss: 0.2134
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.6795
Epoch 1/1... Discriminator Loss: 0.8274... Generator Loss: 1.5282
Epoch 1/1... Discriminator Loss: 1.8828... Generator Loss: 0.2881
Epoch 1/1... Discriminator Loss: 1.4305... Generator Loss: 1.5464
Epoch 1/1... Discriminator Loss: 1.7518... Generator Loss: 0.3131
Epoch 1/1... Discriminator Loss: 1.2469... Generator Loss: 0.7957
Epoch 1/1... Discriminator Loss: 1.3436... Generator Loss: 0.6802
Epoch 1/1... Discriminator Loss: 1.1724... Generator Loss: 1.5688
Epoch 1/1... Discriminator Loss: 1.4320... Generator Loss: 0.5587
Epoch 1/1... Discriminator Loss: 1.3849... Generator Loss: 0.6228
Epoch 1/1... Discriminator Loss: 1.7586... Generator Loss: 0.3597
Epoch 1/1... Discriminator Loss: 1.4858... Generator Loss: 0.7183
Epoch 1/1... Discriminator Loss: 1.4030... Generator Loss: 0.9042
Epoch 1/1... Discriminator Loss: 1.3188... Generator Loss: 1.9639
Epoch 1/1... Discriminator Loss: 1.4706... Generator Loss: 0.5059
Epoch 1/1... Discriminator Loss: 1.3938... Generator Loss: 0.5667
Epoch 1/1... Discriminator Loss: 1.1906... Generator Loss: 0.8984
Epoch 1/1... Discriminator Loss: 1.3652... Generator Loss: 0.8688
Epoch 1/1... Discriminator Loss: 1.3857... Generator Loss: 0.6747
Epoch 1/1... Discriminator Loss: 1.5867... Generator Loss: 0.4757
Epoch 1/1... Discriminator Loss: 1.5661... Generator Loss: 0.8595
Epoch 1/1... Discriminator Loss: 1.4542... Generator Loss: 0.5844
Epoch 1/1... Discriminator Loss: 1.3638... Generator Loss: 1.1092
Epoch 1/1... Discriminator Loss: 1.2551... Generator Loss: 0.8486
Epoch 1/1... Discriminator Loss: 1.6105... Generator Loss: 0.4082
Epoch 1/1... Discriminator Loss: 1.3692... Generator Loss: 1.3560
Epoch 1/1... Discriminator Loss: 1.2128... Generator Loss: 0.6967
Epoch 1/1... Discriminator Loss: 1.3718... Generator Loss: 0.5880
Epoch 1/1... Discriminator Loss: 1.5297... Generator Loss: 0.4517
Epoch 1/1... Discriminator Loss: 1.1109... Generator Loss: 1.4471
Epoch 1/1... Discriminator Loss: 1.1778... Generator Loss: 0.8574
Epoch 1/1... Discriminator Loss: 1.6719... Generator Loss: 0.3698
Epoch 1/1... Discriminator Loss: 1.0960... Generator Loss: 0.9879
Epoch 1/1... Discriminator Loss: 1.2761... Generator Loss: 0.6112
Epoch 1/1... Discriminator Loss: 1.0794... Generator Loss: 0.9234
Epoch 1/1... Discriminator Loss: 1.3843... Generator Loss: 0.9391
Epoch 1/1... Discriminator Loss: 1.3151... Generator Loss: 0.9526
Epoch 1/1... Discriminator Loss: 1.2951... Generator Loss: 0.6288
Epoch 1/1... Discriminator Loss: 1.1560... Generator Loss: 2.3964
Epoch 1/1... Discriminator Loss: 1.3182... Generator Loss: 1.0654
Epoch 1/1... Discriminator Loss: 1.4481... Generator Loss: 0.5591
Epoch 1/1... Discriminator Loss: 1.4443... Generator Loss: 1.4064
Epoch 1/1... Discriminator Loss: 1.3765... Generator Loss: 0.5248
Epoch 1/1... Discriminator Loss: 1.4128... Generator Loss: 0.6235
Epoch 1/1... Discriminator Loss: 1.4219... Generator Loss: 0.7288
Epoch 1/1... Discriminator Loss: 1.0895... Generator Loss: 0.9814
Epoch 1/1... Discriminator Loss: 1.5623... Generator Loss: 0.8755
Epoch 1/1... Discriminator Loss: 1.3884... Generator Loss: 0.6844
Epoch 1/1... Discriminator Loss: 1.4583... Generator Loss: 0.6924
Epoch 1/1... Discriminator Loss: 1.4014... Generator Loss: 0.6966
Epoch 1/1... Discriminator Loss: 1.3890... Generator Loss: 0.6816
Epoch 1/1... Discriminator Loss: 1.2741... Generator Loss: 0.8238
Epoch 1/1... Discriminator Loss: 1.3901... Generator Loss: 0.7822
Epoch 1/1... Discriminator Loss: 1.3690... Generator Loss: 0.5995
Epoch 1/1... Discriminator Loss: 1.2757... Generator Loss: 0.6850
Epoch 1/1... Discriminator Loss: 1.4142... Generator Loss: 0.5553
Epoch 1/1... Discriminator Loss: 1.3474... Generator Loss: 0.9643
Epoch 1/1... Discriminator Loss: 1.2933... Generator Loss: 0.8718
Epoch 1/1... Discriminator Loss: 1.3877... Generator Loss: 0.6573
Epoch 1/1... Discriminator Loss: 1.2465... Generator Loss: 0.9843
Epoch 1/1... Discriminator Loss: 1.3662... Generator Loss: 0.9401
Epoch 1/1... Discriminator Loss: 1.4313... Generator Loss: 0.5808
Epoch 1/1... Discriminator Loss: 1.3066... Generator Loss: 0.7797
Epoch 1/1... Discriminator Loss: 1.3422... Generator Loss: 0.8535
Epoch 1/1... Discriminator Loss: 1.5412... Generator Loss: 1.3817
Epoch 1/1... Discriminator Loss: 1.4780... Generator Loss: 0.5665
Epoch 1/1... Discriminator Loss: 1.3354... Generator Loss: 0.8839
Epoch 1/1... Discriminator Loss: 1.2146... Generator Loss: 0.7222
Epoch 1/1... Discriminator Loss: 1.3380... Generator Loss: 0.5793
Epoch 1/1... Discriminator Loss: 1.3245... Generator Loss: 0.6913
Epoch 1/1... Discriminator Loss: 1.2572... Generator Loss: 0.6960
Epoch 1/1... Discriminator Loss: 1.3297... Generator Loss: 0.7175
Epoch 1/1... Discriminator Loss: 1.4027... Generator Loss: 0.6892
Epoch 1/1... Discriminator Loss: 1.4435... Generator Loss: 1.2444
Epoch 1/1... Discriminator Loss: 1.3813... Generator Loss: 1.0014
Epoch 1/1... Discriminator Loss: 1.3237... Generator Loss: 0.7568
Epoch 1/1... Discriminator Loss: 1.3181... Generator Loss: 0.7520
Epoch 1/1... Discriminator Loss: 1.2348... Generator Loss: 1.0264
Epoch 1/1... Discriminator Loss: 1.3220... Generator Loss: 0.8289
Epoch 1/1... Discriminator Loss: 1.4391... Generator Loss: 0.8644
Epoch 1/1... Discriminator Loss: 1.3629... Generator Loss: 0.6365
Epoch 1/1... Discriminator Loss: 1.0717... Generator Loss: 1.3165
Epoch 1/1... Discriminator Loss: 1.4566... Generator Loss: 0.6454
Epoch 1/1... Discriminator Loss: 1.2953... Generator Loss: 0.8127
Epoch 1/1... Discriminator Loss: 1.1113... Generator Loss: 0.9303
Epoch 1/1... Discriminator Loss: 1.2606... Generator Loss: 0.6721
Epoch 1/1... Discriminator Loss: 1.2761... Generator Loss: 0.6831
Epoch 1/1... Discriminator Loss: 1.1982... Generator Loss: 0.8854
Epoch 1/1... Discriminator Loss: 1.5101... Generator Loss: 0.5034
Epoch 1/1... Discriminator Loss: 1.3656... Generator Loss: 0.5493
Epoch 1/1... Discriminator Loss: 1.2596... Generator Loss: 1.3820
Epoch 1/1... Discriminator Loss: 1.2185... Generator Loss: 0.7481
Epoch 1/1... Discriminator Loss: 1.2938... Generator Loss: 0.7698
Epoch 1/1... Discriminator Loss: 1.2985... Generator Loss: 0.9557
Epoch 1/1... Discriminator Loss: 1.3459... Generator Loss: 0.6200
Epoch 1/1... Discriminator Loss: 1.4400... Generator Loss: 0.4727
Epoch 1/1... Discriminator Loss: 1.2762... Generator Loss: 0.8905
Epoch 1/1... Discriminator Loss: 1.2393... Generator Loss: 0.9596
Epoch 1/1... Discriminator Loss: 1.4636... Generator Loss: 0.4706
Epoch 1/1... Discriminator Loss: 1.2754... Generator Loss: 0.7923
Epoch 1/1... Discriminator Loss: 1.1742... Generator Loss: 0.7971
Epoch 1/1... Discriminator Loss: 1.3400... Generator Loss: 1.5628
Epoch 1/1... Discriminator Loss: 1.2708... Generator Loss: 0.9635
Epoch 1/1... Discriminator Loss: 1.1801... Generator Loss: 1.1304
Epoch 1/1... Discriminator Loss: 1.1162... Generator Loss: 1.5554
Epoch 1/1... Discriminator Loss: 1.2295... Generator Loss: 1.3073
Epoch 1/1... Discriminator Loss: 1.1999... Generator Loss: 0.8917
Epoch 1/1... Discriminator Loss: 1.2692... Generator Loss: 0.7306
Epoch 1/1... Discriminator Loss: 1.2559... Generator Loss: 0.7989
Epoch 1/1... Discriminator Loss: 1.2656... Generator Loss: 1.1861
Epoch 1/1... Discriminator Loss: 1.1984... Generator Loss: 1.1183
Epoch 1/1... Discriminator Loss: 1.5030... Generator Loss: 0.4592
Epoch 1/1... Discriminator Loss: 1.2292... Generator Loss: 1.2808
Epoch 1/1... Discriminator Loss: 1.2726... Generator Loss: 0.7767
Epoch 1/1... Discriminator Loss: 1.2686... Generator Loss: 0.9238
Epoch 1/1... Discriminator Loss: 1.0889... Generator Loss: 1.0602
Epoch 1/1... Discriminator Loss: 1.3686... Generator Loss: 0.6284
Epoch 1/1... Discriminator Loss: 1.3563... Generator Loss: 0.5951
Epoch 1/1... Discriminator Loss: 1.3156... Generator Loss: 0.7043
Epoch 1/1... Discriminator Loss: 1.4448... Generator Loss: 0.5794
Epoch 1/1... Discriminator Loss: 1.2150... Generator Loss: 0.9333
Epoch 1/1... Discriminator Loss: 1.5923... Generator Loss: 0.4016
Epoch 1/1... Discriminator Loss: 1.3285... Generator Loss: 0.9942
Epoch 1/1... Discriminator Loss: 1.1563... Generator Loss: 1.2107
Epoch 1/1... Discriminator Loss: 1.3357... Generator Loss: 0.6240
Epoch 1/1... Discriminator Loss: 1.3377... Generator Loss: 0.6663
Epoch 1/1... Discriminator Loss: 1.6577... Generator Loss: 0.3828
Epoch 1/1... Discriminator Loss: 1.2280... Generator Loss: 0.7264
Epoch 1/1... Discriminator Loss: 1.1370... Generator Loss: 1.2596
Epoch 1/1... Discriminator Loss: 1.3105... Generator Loss: 0.8897
Epoch 1/1... Discriminator Loss: 1.4090... Generator Loss: 0.5980
Epoch 1/1... Discriminator Loss: 1.2825... Generator Loss: 0.8482
Epoch 1/1... Discriminator Loss: 1.3490... Generator Loss: 0.8131
Epoch 1/1... Discriminator Loss: 1.2665... Generator Loss: 0.6497
Epoch 1/1... Discriminator Loss: 1.1249... Generator Loss: 1.0373
Epoch 1/1... Discriminator Loss: 1.0719... Generator Loss: 1.0825
Epoch 1/1... Discriminator Loss: 1.2744... Generator Loss: 0.7772
Epoch 1/1... Discriminator Loss: 1.2962... Generator Loss: 0.9594
Epoch 1/1... Discriminator Loss: 1.4644... Generator Loss: 0.6828
Epoch 1/1... Discriminator Loss: 1.3412... Generator Loss: 0.6068
Epoch 1/1... Discriminator Loss: 1.2668... Generator Loss: 0.8564
Epoch 1/1... Discriminator Loss: 1.6695... Generator Loss: 0.3673
Epoch 1/1... Discriminator Loss: 1.2164... Generator Loss: 0.8302
Epoch 1/1... Discriminator Loss: 1.3058... Generator Loss: 0.7570
Epoch 1/1... Discriminator Loss: 1.1129... Generator Loss: 0.9955
Epoch 1/1... Discriminator Loss: 1.3238... Generator Loss: 1.1267
Epoch 1/1... Discriminator Loss: 1.4320... Generator Loss: 0.5968
Epoch 1/1... Discriminator Loss: 1.2324... Generator Loss: 0.9906
Epoch 1/1... Discriminator Loss: 1.2914... Generator Loss: 0.9545
Epoch 1/1... Discriminator Loss: 1.4238... Generator Loss: 0.7882
Epoch 1/1... Discriminator Loss: 1.2660... Generator Loss: 0.7334
Epoch 1/1... Discriminator Loss: 1.5076... Generator Loss: 0.4867
Epoch 1/1... Discriminator Loss: 1.3751... Generator Loss: 0.6782
Epoch 1/1... Discriminator Loss: 1.2324... Generator Loss: 0.9477
Epoch 1/1... Discriminator Loss: 1.3452... Generator Loss: 0.6266
Epoch 1/1... Discriminator Loss: 1.3867... Generator Loss: 0.6326
Epoch 1/1... Discriminator Loss: 1.1814... Generator Loss: 1.0082
Epoch 1/1... Discriminator Loss: 1.5317... Generator Loss: 0.5176
Epoch 1/1... Discriminator Loss: 1.2901... Generator Loss: 0.7604
Epoch 1/1... Discriminator Loss: 1.3508... Generator Loss: 0.6343
Epoch 1/1... Discriminator Loss: 1.3613... Generator Loss: 0.7953
Epoch 1/1... Discriminator Loss: 1.3240... Generator Loss: 0.7820
Epoch 1/1... Discriminator Loss: 1.4186... Generator Loss: 0.6784
Epoch 1/1... Discriminator Loss: 1.4513... Generator Loss: 0.5864
Epoch 1/1... Discriminator Loss: 1.2972... Generator Loss: 0.7908
Epoch 1/1... Discriminator Loss: 1.3420... Generator Loss: 0.6472
Epoch 1/1... Discriminator Loss: 1.3390... Generator Loss: 0.8927
Epoch 1/1... Discriminator Loss: 1.2505... Generator Loss: 0.7569
Epoch 1/1... Discriminator Loss: 1.3764... Generator Loss: 0.6943
Epoch 1/1... Discriminator Loss: 1.3986... Generator Loss: 0.7109
Epoch 1/1... Discriminator Loss: 1.4294... Generator Loss: 0.6396
Epoch 1/1... Discriminator Loss: 1.3419... Generator Loss: 0.7704
Epoch 1/1... Discriminator Loss: 1.3605... Generator Loss: 0.9163
Epoch 1/1... Discriminator Loss: 1.3888... Generator Loss: 0.6997
Epoch 1/1... Discriminator Loss: 1.3724... Generator Loss: 0.6540
Epoch 1/1... Discriminator Loss: 1.3336... Generator Loss: 0.6917
Epoch 1/1... Discriminator Loss: 1.2352... Generator Loss: 0.9870
Epoch 1/1... Discriminator Loss: 1.3401... Generator Loss: 1.0577
Epoch 1/1... Discriminator Loss: 1.3871... Generator Loss: 0.6913
Epoch 1/1... Discriminator Loss: 1.5025... Generator Loss: 0.5704
Epoch 1/1... Discriminator Loss: 1.1153... Generator Loss: 0.9300
Epoch 1/1... Discriminator Loss: 1.2694... Generator Loss: 1.4819
Epoch 1/1... Discriminator Loss: 1.3391... Generator Loss: 0.6139
Epoch 1/1... Discriminator Loss: 1.2455... Generator Loss: 0.8848
Epoch 1/1... Discriminator Loss: 1.4037... Generator Loss: 0.4961
Epoch 1/1... Discriminator Loss: 1.2706... Generator Loss: 0.8323
Epoch 1/1... Discriminator Loss: 1.4440... Generator Loss: 1.2102
Epoch 1/1... Discriminator Loss: 1.3527... Generator Loss: 0.6144
Epoch 1/1... Discriminator Loss: 1.2512... Generator Loss: 0.9337
Epoch 1/1... Discriminator Loss: 1.2853... Generator Loss: 0.7702
Epoch 1/1... Discriminator Loss: 1.2815... Generator Loss: 0.7735
Epoch 1/1... Discriminator Loss: 1.6039... Generator Loss: 0.4586
Epoch 1/1... Discriminator Loss: 1.1976... Generator Loss: 0.7708
Epoch 1/1... Discriminator Loss: 1.2657... Generator Loss: 0.9189
Epoch 1/1... Discriminator Loss: 1.3719... Generator Loss: 0.6711
Epoch 1/1... Discriminator Loss: 1.3539... Generator Loss: 0.8832
Epoch 1/1... Discriminator Loss: 1.4488... Generator Loss: 0.6680
Epoch 1/1... Discriminator Loss: 1.2160... Generator Loss: 0.8177
Epoch 1/1... Discriminator Loss: 1.3489... Generator Loss: 0.8265
Epoch 1/1... Discriminator Loss: 1.3660... Generator Loss: 0.7476
Epoch 1/1... Discriminator Loss: 1.2886... Generator Loss: 1.0039
Epoch 1/1... Discriminator Loss: 1.4694... Generator Loss: 0.5420
Epoch 1/1... Discriminator Loss: 1.2982... Generator Loss: 0.8408
Epoch 1/1... Discriminator Loss: 1.4762... Generator Loss: 0.6097
Epoch 1/1... Discriminator Loss: 1.2720... Generator Loss: 0.9012
Epoch 1/1... Discriminator Loss: 1.3629... Generator Loss: 0.8207
Epoch 1/1... Discriminator Loss: 1.4395... Generator Loss: 1.2198
Epoch 1/1... Discriminator Loss: 1.1960... Generator Loss: 0.8534
Epoch 1/1... Discriminator Loss: 1.4514... Generator Loss: 0.6711
Epoch 1/1... Discriminator Loss: 1.2431... Generator Loss: 0.7784
Epoch 1/1... Discriminator Loss: 1.2996... Generator Loss: 0.6231
Epoch 1/1... Discriminator Loss: 1.3283... Generator Loss: 0.8876
Epoch 1/1... Discriminator Loss: 1.3340... Generator Loss: 0.7761
Epoch 1/1... Discriminator Loss: 1.2046... Generator Loss: 0.9491
Epoch 1/1... Discriminator Loss: 1.3775... Generator Loss: 0.6008
Epoch 1/1... Discriminator Loss: 1.2816... Generator Loss: 0.7802
Epoch 1/1... Discriminator Loss: 1.4256... Generator Loss: 0.7243
Epoch 1/1... Discriminator Loss: 1.2991... Generator Loss: 0.8855
Epoch 1/1... Discriminator Loss: 1.3763... Generator Loss: 0.6019
Epoch 1/1... Discriminator Loss: 1.5136... Generator Loss: 0.5731
Epoch 1/1... Discriminator Loss: 1.0898... Generator Loss: 1.2597
Epoch 1/1... Discriminator Loss: 1.3536... Generator Loss: 0.6257
Epoch 1/1... Discriminator Loss: 1.3226... Generator Loss: 0.7495
Epoch 1/1... Discriminator Loss: 1.5562... Generator Loss: 0.4657
Epoch 1/1... Discriminator Loss: 1.1037... Generator Loss: 1.3207
Epoch 1/1... Discriminator Loss: 1.4436... Generator Loss: 0.6136
Epoch 1/1... Discriminator Loss: 1.0400... Generator Loss: 1.2721
Epoch 1/1... Discriminator Loss: 1.1624... Generator Loss: 1.2035
Epoch 1/1... Discriminator Loss: 1.2851... Generator Loss: 0.8132
Epoch 1/1... Discriminator Loss: 1.2000... Generator Loss: 0.9151
Epoch 1/1... Discriminator Loss: 1.3267... Generator Loss: 0.6960
Epoch 1/1... Discriminator Loss: 1.2701... Generator Loss: 0.6889
Epoch 1/1... Discriminator Loss: 1.0883... Generator Loss: 1.1004
Epoch 1/1... Discriminator Loss: 1.3079... Generator Loss: 0.8940
Epoch 1/1... Discriminator Loss: 1.3770... Generator Loss: 0.6069
Epoch 1/1... Discriminator Loss: 1.4547... Generator Loss: 0.5658
Epoch 1/1... Discriminator Loss: 1.4584... Generator Loss: 0.4632
Epoch 1/1... Discriminator Loss: 1.2140... Generator Loss: 0.8267
Epoch 1/1... Discriminator Loss: 1.3099... Generator Loss: 0.9403
Epoch 1/1... Discriminator Loss: 1.2562... Generator Loss: 0.6296
Epoch 1/1... Discriminator Loss: 1.2355... Generator Loss: 0.7104
Epoch 1/1... Discriminator Loss: 1.4032... Generator Loss: 0.5571
Epoch 1/1... Discriminator Loss: 1.3668... Generator Loss: 0.6657
Epoch 1/1... Discriminator Loss: 1.1968... Generator Loss: 0.8314
Epoch 1/1... Discriminator Loss: 1.2734... Generator Loss: 0.7924
Epoch 1/1... Discriminator Loss: 1.7601... Generator Loss: 0.3098
Epoch 1/1... Discriminator Loss: 1.2081... Generator Loss: 1.2794
Epoch 1/1... Discriminator Loss: 1.2674... Generator Loss: 0.8973
Epoch 1/1... Discriminator Loss: 1.3319... Generator Loss: 0.8142
Epoch 1/1... Discriminator Loss: 1.2475... Generator Loss: 0.8523
Epoch 1/1... Discriminator Loss: 1.4321... Generator Loss: 0.5511
Epoch 1/1... Discriminator Loss: 1.1781... Generator Loss: 0.9906
Epoch 1/1... Discriminator Loss: 1.2289... Generator Loss: 0.8516
Epoch 1/1... Discriminator Loss: 1.3181... Generator Loss: 0.6913
Epoch 1/1... Discriminator Loss: 1.4690... Generator Loss: 0.5558
Epoch 1/1... Discriminator Loss: 1.2814... Generator Loss: 0.8641
Epoch 1/1... Discriminator Loss: 1.1983... Generator Loss: 0.8295
Epoch 1/1... Discriminator Loss: 1.4000... Generator Loss: 0.6010
Epoch 1/1... Discriminator Loss: 1.4693... Generator Loss: 0.5194
Epoch 1/1... Discriminator Loss: 1.2440... Generator Loss: 1.1426
Epoch 1/1... Discriminator Loss: 1.2750... Generator Loss: 0.7014
Epoch 1/1... Discriminator Loss: 1.2781... Generator Loss: 0.6854
Epoch 1/1... Discriminator Loss: 1.4365... Generator Loss: 0.6572
Epoch 1/1... Discriminator Loss: 1.3454... Generator Loss: 0.9116
Epoch 1/1... Discriminator Loss: 1.0853... Generator Loss: 1.0087
Epoch 1/1... Discriminator Loss: 1.2211... Generator Loss: 0.6699
Epoch 1/1... Discriminator Loss: 1.4927... Generator Loss: 0.5094
Epoch 1/1... Discriminator Loss: 1.3770... Generator Loss: 0.5813
Epoch 1/1... Discriminator Loss: 1.3260... Generator Loss: 0.8547
Epoch 1/1... Discriminator Loss: 1.3674... Generator Loss: 0.6320
Epoch 1/1... Discriminator Loss: 1.1712... Generator Loss: 1.1169
Epoch 1/1... Discriminator Loss: 1.3092... Generator Loss: 0.6072
Epoch 1/1... Discriminator Loss: 1.3058... Generator Loss: 0.7328
Epoch 1/1... Discriminator Loss: 1.3107... Generator Loss: 0.7448
Epoch 1/1... Discriminator Loss: 1.3206... Generator Loss: 0.6152
Epoch 1/1... Discriminator Loss: 1.3334... Generator Loss: 0.8092
Epoch 1/1... Discriminator Loss: 1.4074... Generator Loss: 0.6370
Epoch 1/1... Discriminator Loss: 1.3723... Generator Loss: 0.9073
Epoch 1/1... Discriminator Loss: 1.2966... Generator Loss: 0.7645
Epoch 1/1... Discriminator Loss: 1.3621... Generator Loss: 0.7179
Epoch 1/1... Discriminator Loss: 1.3404... Generator Loss: 0.7294
Epoch 1/1... Discriminator Loss: 1.2639... Generator Loss: 0.7075
Epoch 1/1... Discriminator Loss: 1.3008... Generator Loss: 0.6555
Epoch 1/1... Discriminator Loss: 1.2799... Generator Loss: 0.7760
Epoch 1/1... Discriminator Loss: 1.2764... Generator Loss: 0.6146
Epoch 1/1... Discriminator Loss: 1.2257... Generator Loss: 0.8716
Epoch 1/1... Discriminator Loss: 1.1867... Generator Loss: 1.2057
Epoch 1/1... Discriminator Loss: 1.4374... Generator Loss: 0.6205
Epoch 1/1... Discriminator Loss: 1.3250... Generator Loss: 1.0081
Epoch 1/1... Discriminator Loss: 1.2149... Generator Loss: 0.9421
Epoch 1/1... Discriminator Loss: 1.2199... Generator Loss: 0.8867
Epoch 1/1... Discriminator Loss: 1.2628... Generator Loss: 1.4038
Epoch 1/1... Discriminator Loss: 1.3949... Generator Loss: 0.7701
Epoch 1/1... Discriminator Loss: 1.4848... Generator Loss: 0.4776
Epoch 1/1... Discriminator Loss: 1.5439... Generator Loss: 0.5020
Epoch 1/1... Discriminator Loss: 1.1940... Generator Loss: 0.9669
Epoch 1/1... Discriminator Loss: 1.1713... Generator Loss: 0.7835
Epoch 1/1... Discriminator Loss: 1.4093... Generator Loss: 0.6014
Epoch 1/1... Discriminator Loss: 1.1358... Generator Loss: 1.1020
Epoch 1/1... Discriminator Loss: 0.9587... Generator Loss: 1.0086
Epoch 1/1... Discriminator Loss: 1.0952... Generator Loss: 0.8414
Epoch 1/1... Discriminator Loss: 1.2274... Generator Loss: 0.6458
Epoch 1/1... Discriminator Loss: 1.1113... Generator Loss: 1.1676
Epoch 1/1... Discriminator Loss: 1.5076... Generator Loss: 0.8539
Epoch 1/1... Discriminator Loss: 1.5469... Generator Loss: 0.4827
Epoch 1/1... Discriminator Loss: 1.3708... Generator Loss: 0.5333
Epoch 1/1... Discriminator Loss: 1.4471... Generator Loss: 0.5166
Epoch 1/1... Discriminator Loss: 1.1355... Generator Loss: 1.0198
Epoch 1/1... Discriminator Loss: 1.5294... Generator Loss: 0.4597
Epoch 1/1... Discriminator Loss: 1.3734... Generator Loss: 0.6592
Epoch 1/1... Discriminator Loss: 1.1930... Generator Loss: 0.7252
Epoch 1/1... Discriminator Loss: 1.2415... Generator Loss: 0.6825
Epoch 1/1... Discriminator Loss: 1.3554... Generator Loss: 0.6411
Epoch 1/1... Discriminator Loss: 1.3669... Generator Loss: 0.6520
Epoch 1/1... Discriminator Loss: 1.4829... Generator Loss: 0.8908
Epoch 1/1... Discriminator Loss: 1.4521... Generator Loss: 0.4746
Epoch 1/1... Discriminator Loss: 1.1411... Generator Loss: 1.0835
Epoch 1/1... Discriminator Loss: 1.4785... Generator Loss: 0.9801
Epoch 1/1... Discriminator Loss: 1.3021... Generator Loss: 1.0200
Epoch 1/1... Discriminator Loss: 1.1493... Generator Loss: 0.9458
Epoch 1/1... Discriminator Loss: 1.4238... Generator Loss: 1.5467
Epoch 1/1... Discriminator Loss: 1.2612... Generator Loss: 1.3691
Epoch 1/1... Discriminator Loss: 1.1705... Generator Loss: 1.1198
Epoch 1/1... Discriminator Loss: 1.1987... Generator Loss: 1.2617
Epoch 1/1... Discriminator Loss: 1.0409... Generator Loss: 1.0246
Epoch 1/1... Discriminator Loss: 1.3188... Generator Loss: 0.9242
Epoch 1/1... Discriminator Loss: 1.2737... Generator Loss: 0.7641
Epoch 1/1... Discriminator Loss: 1.3933... Generator Loss: 0.5305
Epoch 1/1... Discriminator Loss: 1.4080... Generator Loss: 0.5278
Epoch 1/1... Discriminator Loss: 1.6991... Generator Loss: 0.3349
Epoch 1/1... Discriminator Loss: 1.1199... Generator Loss: 0.8831
Epoch 1/1... Discriminator Loss: 1.2854... Generator Loss: 0.9352
Epoch 1/1... Discriminator Loss: 1.3897... Generator Loss: 0.5392
Epoch 1/1... Discriminator Loss: 1.0456... Generator Loss: 1.1959
Epoch 1/1... Discriminator Loss: 1.3865... Generator Loss: 0.5991
Epoch 1/1... Discriminator Loss: 1.5396... Generator Loss: 0.4627
Epoch 1/1... Discriminator Loss: 1.2854... Generator Loss: 0.7319
Epoch 1/1... Discriminator Loss: 1.4741... Generator Loss: 0.5618
Epoch 1/1... Discriminator Loss: 1.4983... Generator Loss: 0.8548
Epoch 1/1... Discriminator Loss: 1.1370... Generator Loss: 0.9328
Epoch 1/1... Discriminator Loss: 1.0576... Generator Loss: 1.2943
Epoch 1/1... Discriminator Loss: 1.3148... Generator Loss: 0.6704
Epoch 1/1... Discriminator Loss: 1.3459... Generator Loss: 0.6592
Epoch 1/1... Discriminator Loss: 1.2965... Generator Loss: 0.6184
Epoch 1/1... Discriminator Loss: 1.1663... Generator Loss: 0.9067
Epoch 1/1... Discriminator Loss: 1.3509... Generator Loss: 1.1307
Epoch 1/1... Discriminator Loss: 1.2973... Generator Loss: 0.7646
Epoch 1/1... Discriminator Loss: 1.2389... Generator Loss: 0.6920
Epoch 1/1... Discriminator Loss: 1.2658... Generator Loss: 0.6849
Epoch 1/1... Discriminator Loss: 1.2974... Generator Loss: 0.7162
Epoch 1/1... Discriminator Loss: 1.2709... Generator Loss: 0.6868
Epoch 1/1... Discriminator Loss: 1.4871... Generator Loss: 0.6419
Epoch 1/1... Discriminator Loss: 1.3133... Generator Loss: 0.9861
Epoch 1/1... Discriminator Loss: 1.2522... Generator Loss: 0.8031
Epoch 1/1... Discriminator Loss: 1.5458... Generator Loss: 0.4459
Epoch 1/1... Discriminator Loss: 1.1948... Generator Loss: 0.9834
Epoch 1/1... Discriminator Loss: 1.4282... Generator Loss: 0.5772
Epoch 1/1... Discriminator Loss: 1.2564... Generator Loss: 0.7185
Epoch 1/1... Discriminator Loss: 0.9288... Generator Loss: 1.0841
Epoch 1/1... Discriminator Loss: 1.4348... Generator Loss: 0.6059
Epoch 1/1... Discriminator Loss: 1.3002... Generator Loss: 0.9454
Epoch 1/1... Discriminator Loss: 1.1112... Generator Loss: 1.4154
Epoch 1/1... Discriminator Loss: 1.2795... Generator Loss: 0.6934
Epoch 1/1... Discriminator Loss: 1.2826... Generator Loss: 0.8118
Epoch 1/1... Discriminator Loss: 1.4692... Generator Loss: 0.6335
Epoch 1/1... Discriminator Loss: 1.3644... Generator Loss: 0.8622
Epoch 1/1... Discriminator Loss: 1.3076... Generator Loss: 0.6536
Epoch 1/1... Discriminator Loss: 1.2329... Generator Loss: 0.7350
Epoch 1/1... Discriminator Loss: 1.2647... Generator Loss: 0.7946
Epoch 1/1... Discriminator Loss: 1.2484... Generator Loss: 0.9734
Epoch 1/1... Discriminator Loss: 1.3417... Generator Loss: 0.5761
Epoch 1/1... Discriminator Loss: 1.3127... Generator Loss: 0.6745
Epoch 1/1... Discriminator Loss: 1.4090... Generator Loss: 0.5587
Epoch 1/1... Discriminator Loss: 1.1853... Generator Loss: 0.9338
Epoch 1/1... Discriminator Loss: 1.1569... Generator Loss: 0.8097
Epoch 1/1... Discriminator Loss: 1.2077... Generator Loss: 0.8662
Epoch 1/1... Discriminator Loss: 1.8161... Generator Loss: 0.5223
Epoch 1/1... Discriminator Loss: 1.2440... Generator Loss: 1.1375
Epoch 1/1... Discriminator Loss: 1.2101... Generator Loss: 0.7860
Epoch 1/1... Discriminator Loss: 1.3924... Generator Loss: 0.5612
Epoch 1/1... Discriminator Loss: 1.3483... Generator Loss: 0.6328
Epoch 1/1... Discriminator Loss: 1.5084... Generator Loss: 0.5571
Epoch 1/1... Discriminator Loss: 1.3257... Generator Loss: 0.7324
Epoch 1/1... Discriminator Loss: 1.3989... Generator Loss: 0.6554
Epoch 1/1... Discriminator Loss: 1.4948... Generator Loss: 0.6766
Epoch 1/1... Discriminator Loss: 1.3827... Generator Loss: 0.5588
Epoch 1/1... Discriminator Loss: 1.1645... Generator Loss: 0.9704
Epoch 1/1... Discriminator Loss: 1.3581... Generator Loss: 0.6125
Epoch 1/1... Discriminator Loss: 1.2044... Generator Loss: 0.8467
Epoch 1/1... Discriminator Loss: 1.3524... Generator Loss: 0.6837
Epoch 1/1... Discriminator Loss: 1.4678... Generator Loss: 0.6504
Epoch 1/1... Discriminator Loss: 1.2434... Generator Loss: 0.7167
Epoch 1/1... Discriminator Loss: 1.2096... Generator Loss: 0.8229
Epoch 1/1... Discriminator Loss: 1.4072... Generator Loss: 0.5589
Epoch 1/1... Discriminator Loss: 1.2566... Generator Loss: 0.7561
Epoch 1/1... Discriminator Loss: 1.4313... Generator Loss: 0.6483
Epoch 1/1... Discriminator Loss: 1.2338... Generator Loss: 0.9379
Epoch 1/1... Discriminator Loss: 1.2938... Generator Loss: 0.8276
Epoch 1/1... Discriminator Loss: 1.1867... Generator Loss: 0.8905
Epoch 1/1... Discriminator Loss: 1.3032... Generator Loss: 0.7660
Epoch 1/1... Discriminator Loss: 1.2942... Generator Loss: 0.6186
Epoch 1/1... Discriminator Loss: 1.4355... Generator Loss: 0.6153
Epoch 1/1... Discriminator Loss: 1.4064... Generator Loss: 0.6663
Epoch 1/1... Discriminator Loss: 1.3634... Generator Loss: 0.7271
Epoch 1/1... Discriminator Loss: 1.1040... Generator Loss: 1.2044
Epoch 1/1... Discriminator Loss: 1.3036... Generator Loss: 0.6607
Epoch 1/1... Discriminator Loss: 1.2891... Generator Loss: 0.7421
Epoch 1/1... Discriminator Loss: 1.3155... Generator Loss: 0.7632
Epoch 1/1... Discriminator Loss: 1.3592... Generator Loss: 0.5526
Epoch 1/1... Discriminator Loss: 1.3430... Generator Loss: 0.7035
Epoch 1/1... Discriminator Loss: 1.1492... Generator Loss: 0.8527
Epoch 1/1... Discriminator Loss: 1.5374... Generator Loss: 0.4275
Epoch 1/1... Discriminator Loss: 1.5574... Generator Loss: 0.4307
Epoch 1/1... Discriminator Loss: 1.3374... Generator Loss: 0.7950
Epoch 1/1... Discriminator Loss: 1.2663... Generator Loss: 0.8339
Epoch 1/1... Discriminator Loss: 1.2958... Generator Loss: 0.9522
Epoch 1/1... Discriminator Loss: 1.4683... Generator Loss: 0.5435
Epoch 1/1... Discriminator Loss: 1.2844... Generator Loss: 0.7954
Epoch 1/1... Discriminator Loss: 1.3161... Generator Loss: 0.7979
Epoch 1/1... Discriminator Loss: 1.3083... Generator Loss: 0.7004
Epoch 1/1... Discriminator Loss: 1.5325... Generator Loss: 0.4446
Epoch 1/1... Discriminator Loss: 1.3961... Generator Loss: 0.6387
Epoch 1/1... Discriminator Loss: 1.3978... Generator Loss: 1.1955
Epoch 1/1... Discriminator Loss: 1.0127... Generator Loss: 1.2267
Epoch 1/1... Discriminator Loss: 1.0862... Generator Loss: 0.9409
Epoch 1/1... Discriminator Loss: 1.2200... Generator Loss: 0.7279
Epoch 1/1... Discriminator Loss: 1.1952... Generator Loss: 0.8615
Epoch 1/1... Discriminator Loss: 1.1141... Generator Loss: 0.7936
Epoch 1/1... Discriminator Loss: 1.2803... Generator Loss: 0.6518
Epoch 1/1... Discriminator Loss: 1.2975... Generator Loss: 1.0989
Epoch 1/1... Discriminator Loss: 1.0133... Generator Loss: 1.0388
Epoch 1/1... Discriminator Loss: 1.3109... Generator Loss: 0.6041
Epoch 1/1... Discriminator Loss: 1.1314... Generator Loss: 0.9456
Epoch 1/1... Discriminator Loss: 1.2507... Generator Loss: 1.1139
Epoch 1/1... Discriminator Loss: 1.1494... Generator Loss: 0.9431
Epoch 1/1... Discriminator Loss: 1.4908... Generator Loss: 0.4753
Epoch 1/1... Discriminator Loss: 1.2319... Generator Loss: 0.8887
Epoch 1/1... Discriminator Loss: 1.5230... Generator Loss: 0.8982
Epoch 1/1... Discriminator Loss: 1.3057... Generator Loss: 0.8080
Epoch 1/1... Discriminator Loss: 1.4768... Generator Loss: 0.5201
Epoch 1/1... Discriminator Loss: 1.0686... Generator Loss: 1.4617
Epoch 1/1... Discriminator Loss: 1.2645... Generator Loss: 0.7664
Epoch 1/1... Discriminator Loss: 1.3718... Generator Loss: 0.5789
Epoch 1/1... Discriminator Loss: 1.4091... Generator Loss: 0.5953
Epoch 1/1... Discriminator Loss: 1.3218... Generator Loss: 0.6936
Epoch 1/1... Discriminator Loss: 1.3060... Generator Loss: 0.7676
Epoch 1/1... Discriminator Loss: 1.3816... Generator Loss: 0.5949
Epoch 1/1... Discriminator Loss: 1.2399... Generator Loss: 0.7975
Epoch 1/1... Discriminator Loss: 1.2636... Generator Loss: 0.9467
Epoch 1/1... Discriminator Loss: 1.3724... Generator Loss: 0.7492
Epoch 1/1... Discriminator Loss: 1.2016... Generator Loss: 0.6474
Epoch 1/1... Discriminator Loss: 1.3361... Generator Loss: 1.5712
Epoch 1/1... Discriminator Loss: 1.2398... Generator Loss: 1.0196
Epoch 1/1... Discriminator Loss: 1.3193... Generator Loss: 0.6949
Epoch 1/1... Discriminator Loss: 1.4845... Generator Loss: 0.5990
Epoch 1/1... Discriminator Loss: 1.2605... Generator Loss: 0.9118
Epoch 1/1... Discriminator Loss: 1.2890... Generator Loss: 0.8128
Epoch 1/1... Discriminator Loss: 1.1490... Generator Loss: 0.8407
Epoch 1/1... Discriminator Loss: 1.0339... Generator Loss: 1.0836
Epoch 1/1... Discriminator Loss: 1.7789... Generator Loss: 0.3101
Epoch 1/1... Discriminator Loss: 1.1684... Generator Loss: 0.9869
Epoch 1/1... Discriminator Loss: 1.3253... Generator Loss: 0.6013
Epoch 1/1... Discriminator Loss: 1.2276... Generator Loss: 0.8998
Epoch 1/1... Discriminator Loss: 1.2359... Generator Loss: 0.7060
Epoch 1/1... Discriminator Loss: 1.2296... Generator Loss: 0.7323
Epoch 1/1... Discriminator Loss: 1.2249... Generator Loss: 0.7231
Epoch 1/1... Discriminator Loss: 1.2478... Generator Loss: 0.8735
Epoch 1/1... Discriminator Loss: 1.5431... Generator Loss: 0.4461
Epoch 1/1... Discriminator Loss: 1.2206... Generator Loss: 0.7614
Epoch 1/1... Discriminator Loss: 1.2981... Generator Loss: 0.8575
Epoch 1/1... Discriminator Loss: 1.2082... Generator Loss: 1.0869
Epoch 1/1... Discriminator Loss: 1.3233... Generator Loss: 0.6065
Epoch 1/1... Discriminator Loss: 1.1876... Generator Loss: 1.0415
Epoch 1/1... Discriminator Loss: 1.3575... Generator Loss: 0.7276
Epoch 1/1... Discriminator Loss: 1.3409... Generator Loss: 0.7251
Epoch 1/1... Discriminator Loss: 1.4120... Generator Loss: 0.5703
Epoch 1/1... Discriminator Loss: 1.4527... Generator Loss: 0.4854
Epoch 1/1... Discriminator Loss: 1.4230... Generator Loss: 0.7441
Epoch 1/1... Discriminator Loss: 1.3774... Generator Loss: 0.6001
Epoch 1/1... Discriminator Loss: 1.4134... Generator Loss: 0.5437
Epoch 1/1... Discriminator Loss: 1.4481... Generator Loss: 0.6021
Epoch 1/1... Discriminator Loss: 1.3552... Generator Loss: 0.5769
Epoch 1/1... Discriminator Loss: 1.3637... Generator Loss: 0.6421
Epoch 1/1... Discriminator Loss: 1.3884... Generator Loss: 0.6002
Epoch 1/1... Discriminator Loss: 1.3482... Generator Loss: 0.6947
Epoch 1/1... Discriminator Loss: 1.2898... Generator Loss: 0.7535
Epoch 1/1... Discriminator Loss: 1.2980... Generator Loss: 0.7967
Epoch 1/1... Discriminator Loss: 1.2737... Generator Loss: 0.6625
Epoch 1/1... Discriminator Loss: 1.3301... Generator Loss: 0.6339
Epoch 1/1... Discriminator Loss: 1.2823... Generator Loss: 0.7065
Epoch 1/1... Discriminator Loss: 1.4071... Generator Loss: 0.6767
Epoch 1/1... Discriminator Loss: 1.3755... Generator Loss: 0.6173
Epoch 1/1... Discriminator Loss: 1.3385... Generator Loss: 0.6545
Epoch 1/1... Discriminator Loss: 1.3192... Generator Loss: 0.7610
Epoch 1/1... Discriminator Loss: 1.5344... Generator Loss: 0.4805
Epoch 1/1... Discriminator Loss: 1.3671... Generator Loss: 0.7482
Epoch 1/1... Discriminator Loss: 1.6222... Generator Loss: 0.4425
Epoch 1/1... Discriminator Loss: 1.4575... Generator Loss: 0.7051
Epoch 1/1... Discriminator Loss: 1.2887... Generator Loss: 0.8226
Epoch 1/1... Discriminator Loss: 1.3465... Generator Loss: 0.6749
Epoch 1/1... Discriminator Loss: 1.3821... Generator Loss: 0.6813
Epoch 1/1... Discriminator Loss: 1.3602... Generator Loss: 0.7118
Epoch 1/1... Discriminator Loss: 1.2860... Generator Loss: 0.8281
Epoch 1/1... Discriminator Loss: 1.3489... Generator Loss: 0.7532
Epoch 1/1... Discriminator Loss: 1.5112... Generator Loss: 0.5076
Epoch 1/1... Discriminator Loss: 1.3704... Generator Loss: 0.6493
Epoch 1/1... Discriminator Loss: 1.4293... Generator Loss: 0.5889
Epoch 1/1... Discriminator Loss: 1.4166... Generator Loss: 0.6361
Epoch 1/1... Discriminator Loss: 1.3559... Generator Loss: 0.6875
Epoch 1/1... Discriminator Loss: 1.3724... Generator Loss: 0.6429
Epoch 1/1... Discriminator Loss: 1.3225... Generator Loss: 0.7885
Epoch 1/1... Discriminator Loss: 1.3680... Generator Loss: 0.6329
Epoch 1/1... Discriminator Loss: 1.3737... Generator Loss: 0.6203
Epoch 1/1... Discriminator Loss: 1.3169... Generator Loss: 0.6882
Epoch 1/1... Discriminator Loss: 1.1437... Generator Loss: 0.8723
Epoch 1/1... Discriminator Loss: 1.3870... Generator Loss: 0.5303
Epoch 1/1... Discriminator Loss: 1.3282... Generator Loss: 0.7164
Epoch 1/1... Discriminator Loss: 1.3970... Generator Loss: 0.7112
Epoch 1/1... Discriminator Loss: 1.1717... Generator Loss: 0.8893
Epoch 1/1... Discriminator Loss: 1.4969... Generator Loss: 0.5431
Epoch 1/1... Discriminator Loss: 1.3598... Generator Loss: 0.7212
Epoch 1/1... Discriminator Loss: 1.2452... Generator Loss: 0.7839
Epoch 1/1... Discriminator Loss: 1.2634... Generator Loss: 0.7888
Epoch 1/1... Discriminator Loss: 1.3228... Generator Loss: 0.7293
Epoch 1/1... Discriminator Loss: 1.1527... Generator Loss: 0.9826
Epoch 1/1... Discriminator Loss: 1.4382... Generator Loss: 0.7264
Epoch 1/1... Discriminator Loss: 1.1521... Generator Loss: 0.9670
Epoch 1/1... Discriminator Loss: 1.2389... Generator Loss: 0.8754
Epoch 1/1... Discriminator Loss: 1.3515... Generator Loss: 0.6336
Epoch 1/1... Discriminator Loss: 1.4193... Generator Loss: 0.6799
Epoch 1/1... Discriminator Loss: 1.3967... Generator Loss: 0.7326
Epoch 1/1... Discriminator Loss: 1.4975... Generator Loss: 0.4735
Epoch 1/1... Discriminator Loss: 1.3778... Generator Loss: 0.7378
Epoch 1/1... Discriminator Loss: 1.4908... Generator Loss: 0.4982
Epoch 1/1... Discriminator Loss: 1.2810... Generator Loss: 0.7309
Epoch 1/1... Discriminator Loss: 1.2859... Generator Loss: 0.7729
Epoch 1/1... Discriminator Loss: 1.3723... Generator Loss: 0.6847
Epoch 1/1... Discriminator Loss: 1.2226... Generator Loss: 0.8219
Epoch 1/1... Discriminator Loss: 1.2526... Generator Loss: 0.7491
Epoch 1/1... Discriminator Loss: 1.4910... Generator Loss: 0.4709
Epoch 1/1... Discriminator Loss: 1.2529... Generator Loss: 1.0243
Epoch 1/1... Discriminator Loss: 1.3943... Generator Loss: 0.5903
Epoch 1/1... Discriminator Loss: 1.4748... Generator Loss: 0.5400
Epoch 1/1... Discriminator Loss: 1.2261... Generator Loss: 0.7905
Epoch 1/1... Discriminator Loss: 1.3130... Generator Loss: 0.7411
Epoch 1/1... Discriminator Loss: 1.4140... Generator Loss: 0.5929
Epoch 1/1... Discriminator Loss: 1.3041... Generator Loss: 0.6953
Epoch 1/1... Discriminator Loss: 1.3597... Generator Loss: 0.5891
Epoch 1/1... Discriminator Loss: 1.4109... Generator Loss: 0.5955
Epoch 1/1... Discriminator Loss: 1.1366... Generator Loss: 0.8613
Epoch 1/1... Discriminator Loss: 1.3682... Generator Loss: 0.7280
Epoch 1/1... Discriminator Loss: 1.2762... Generator Loss: 0.9194
Epoch 1/1... Discriminator Loss: 1.4156... Generator Loss: 0.6259
Epoch 1/1... Discriminator Loss: 1.4607... Generator Loss: 0.6718
Epoch 1/1... Discriminator Loss: 1.5958... Generator Loss: 0.4333
Epoch 1/1... Discriminator Loss: 1.3452... Generator Loss: 0.6697
Epoch 1/1... Discriminator Loss: 1.3064... Generator Loss: 0.8525
Epoch 1/1... Discriminator Loss: 1.4202... Generator Loss: 0.5715
Epoch 1/1... Discriminator Loss: 1.2368... Generator Loss: 0.7633
Epoch 1/1... Discriminator Loss: 1.2476... Generator Loss: 0.6901
Epoch 1/1... Discriminator Loss: 1.0076... Generator Loss: 1.1468
Epoch 1/1... Discriminator Loss: 1.3747... Generator Loss: 0.5943
Epoch 1/1... Discriminator Loss: 1.3305... Generator Loss: 0.7851
Epoch 1/1... Discriminator Loss: 1.3209... Generator Loss: 0.6204
Epoch 1/1... Discriminator Loss: 1.3836... Generator Loss: 0.6374
Epoch 1/1... Discriminator Loss: 1.0983... Generator Loss: 1.0322
Epoch 1/1... Discriminator Loss: 1.4964... Generator Loss: 0.4854
Epoch 1/1... Discriminator Loss: 1.1658... Generator Loss: 1.0355
Epoch 1/1... Discriminator Loss: 1.0558... Generator Loss: 1.0404
Epoch 1/1... Discriminator Loss: 1.5019... Generator Loss: 0.8579
Epoch 1/1... Discriminator Loss: 1.0497... Generator Loss: 0.9340
Epoch 1/1... Discriminator Loss: 1.2453... Generator Loss: 0.9171
Epoch 1/1... Discriminator Loss: 1.1702... Generator Loss: 0.8659
Epoch 1/1... Discriminator Loss: 1.4748... Generator Loss: 0.5423
Epoch 1/1... Discriminator Loss: 1.3216... Generator Loss: 0.6779
Epoch 1/1... Discriminator Loss: 1.1996... Generator Loss: 0.6783
Epoch 1/1... Discriminator Loss: 1.5341... Generator Loss: 0.4586
Epoch 1/1... Discriminator Loss: 1.3306... Generator Loss: 0.5487
Epoch 1/1... Discriminator Loss: 1.0819... Generator Loss: 1.3698
Epoch 1/1... Discriminator Loss: 1.4083... Generator Loss: 0.9636
Epoch 1/1... Discriminator Loss: 1.2815... Generator Loss: 0.6576
Epoch 1/1... Discriminator Loss: 1.4889... Generator Loss: 0.4618
Epoch 1/1... Discriminator Loss: 1.2358... Generator Loss: 0.6901
Epoch 1/1... Discriminator Loss: 1.5272... Generator Loss: 0.4607
Epoch 1/1... Discriminator Loss: 1.5253... Generator Loss: 0.4908
Epoch 1/1... Discriminator Loss: 1.0693... Generator Loss: 1.1704
Epoch 1/1... Discriminator Loss: 1.2894... Generator Loss: 0.7047
Epoch 1/1... Discriminator Loss: 1.4082... Generator Loss: 0.7714
Epoch 1/1... Discriminator Loss: 1.4700... Generator Loss: 0.5466
Epoch 1/1... Discriminator Loss: 1.4014... Generator Loss: 0.5095
Epoch 1/1... Discriminator Loss: 1.2658... Generator Loss: 0.7207
Epoch 1/1... Discriminator Loss: 1.3340... Generator Loss: 0.6213
Epoch 1/1... Discriminator Loss: 1.4584... Generator Loss: 0.5425
Epoch 1/1... Discriminator Loss: 1.4428... Generator Loss: 0.5245
Epoch 1/1... Discriminator Loss: 1.3378... Generator Loss: 0.6580
Epoch 1/1... Discriminator Loss: 1.2357... Generator Loss: 0.6520
Epoch 1/1... Discriminator Loss: 1.1308... Generator Loss: 0.7951
Epoch 1/1... Discriminator Loss: 1.0828... Generator Loss: 0.8403
Epoch 1/1... Discriminator Loss: 1.1614... Generator Loss: 1.0686
Epoch 1/1... Discriminator Loss: 1.7597... Generator Loss: 0.3628
Epoch 1/1... Discriminator Loss: 1.3227... Generator Loss: 1.2271
Epoch 1/1... Discriminator Loss: 1.2398... Generator Loss: 0.7657
Epoch 1/1... Discriminator Loss: 1.1968... Generator Loss: 1.0541
Epoch 1/1... Discriminator Loss: 1.1842... Generator Loss: 0.8516
Epoch 1/1... Discriminator Loss: 1.2648... Generator Loss: 0.7444
Epoch 1/1... Discriminator Loss: 1.2632... Generator Loss: 0.9243
Epoch 1/1... Discriminator Loss: 1.3717... Generator Loss: 0.6045
Epoch 1/1... Discriminator Loss: 1.5272... Generator Loss: 0.4455
Epoch 1/1... Discriminator Loss: 1.0595... Generator Loss: 0.9192
Epoch 1/1... Discriminator Loss: 1.2614... Generator Loss: 1.0954
Epoch 1/1... Discriminator Loss: 1.5416... Generator Loss: 0.4555
Epoch 1/1... Discriminator Loss: 1.5012... Generator Loss: 0.4965
Epoch 1/1... Discriminator Loss: 1.0613... Generator Loss: 1.2813
Epoch 1/1... Discriminator Loss: 1.4339... Generator Loss: 0.5232
Epoch 1/1... Discriminator Loss: 1.2807... Generator Loss: 0.6386
Epoch 1/1... Discriminator Loss: 1.6815... Generator Loss: 0.3554
Epoch 1/1... Discriminator Loss: 1.4725... Generator Loss: 0.5913
Epoch 1/1... Discriminator Loss: 1.1705... Generator Loss: 1.2657
Epoch 1/1... Discriminator Loss: 1.2626... Generator Loss: 0.6224
Epoch 1/1... Discriminator Loss: 1.3393... Generator Loss: 0.6689
Epoch 1/1... Discriminator Loss: 1.2416... Generator Loss: 0.7840
Epoch 1/1... Discriminator Loss: 1.2743... Generator Loss: 0.7531
Epoch 1/1... Discriminator Loss: 1.3185... Generator Loss: 0.6441
Epoch 1/1... Discriminator Loss: 1.3614... Generator Loss: 0.5898
Epoch 1/1... Discriminator Loss: 1.3527... Generator Loss: 0.6170
Epoch 1/1... Discriminator Loss: 1.2196... Generator Loss: 0.9103
Epoch 1/1... Discriminator Loss: 1.2818... Generator Loss: 0.7540
Epoch 1/1... Discriminator Loss: 1.7204... Generator Loss: 0.4770
Epoch 1/1... Discriminator Loss: 1.2163... Generator Loss: 0.7635
Epoch 1/1... Discriminator Loss: 1.3057... Generator Loss: 0.6519

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.